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Seismic data can improve the stochastic facies modelling significantly

Charlotte B. Tjølsen, G. Jonhsen, Gunnar Halvorsen

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Abstract

Heterogeneous reservoir units comprising fluvial channel sandstones in vertical and lateral alternation with finer grained, non-reservoir lithologies pose a serious problem to dedicated production drilling and field development planning. The exact interwell position of each reservoir sandstone body can in most cases be only indirectly assessed through conventional geological well-correlation and mapping, and the potential of drilling unsuccessful production wells is usually present. The scope of this paper is to present a new technique which ensures that information obtained from 3D seismic surveys is fully utilized in the discrete facies modelling of fluvial sandstone bodies in a heterogeneous reservoir unit. We show that there is a useful, empirical relationship between the seismic impedance and the facies (channel sandstones/non-reservoir). Notably, there is a high probability of obtaining channels in low impedance regions, whereas high impedance areas have a lower probability of channels. This relationship is utilized to guide the discrete modelling of channels. An example from a fluvial North Sea reservoir is presented. The use of seismic data as an additional source of conditioning data reduces the uncertainty in the stochastic reservoir model, since the uncertainty in the reservoir description in the interwell areas is significantly reduced.

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Heterogeneous reservoir units comprising fluvial channel sandstones in vertical and lateral alternation with finer grained, non-reservoir lithologies pose a serious problem to dedicated production drilling and field development planning. The exact interwell position of each reservoir sandstone body can in most cases be only indirectly assessed through conventional geological well-correlation and mapping, and the potential of drilling unsuccessful production wells is usually present. The scope of this paper is to present a new technique which ensures that information obtained from 3D seismic surveys is fully utilized in the discrete facies modelling of fluvial sandstone bodies in a heterogeneous reservoir unit. We show that there is a useful, empirical relationship between the seismic impedance and the facies (channel sandstones/non-reservoir). Notably, there is a high probability of obtaining channels in low impedance regions, whereas high impedance areas have a lower probability of channels. This relationship is utilized to guide the discrete modelling of channels. An example from a fluvial North Sea reservoir is presented. The use of seismic data as an additional source of conditioning data reduces the uncertainty in the stochastic reservoir model, since the uncertainty in the reservoir description in the interwell areas is significantly reduced.

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Available abstract

Heterogeneous reservoir units comprising fluvial channel sandstones in vertical and lateral alternation with finer grained, non-reservoir lithologies pose a serious problem to dedicated production drilling and field development planning. The exact interwell position of each reservoir sandstone body can in most cases be only indirectly assessed through conventional geological well-correlation and mapping, and the potential of drilling unsuccessful production wells is usually present. The scope of this paper is to present a new technique which ensures that information obtained from 3D seismic surveys is fully utilized in the discrete facies modelling of fluvial sandstone bodies in a heterogeneous reservoir unit. We show that there is a useful, empirical relationship between the seismic impedance and the facies (channel sandstones/non-reservoir). Notably, there is a high probability of obtaining channels in low impedance regions, whereas high impedance areas have a lower probability of channels. This relationship is utilized to guide the discrete modelling of channels. An example from a fluvial North Sea reservoir is presented. The use of seismic data as an additional source of conditioning data reduces the uncertainty in the stochastic reservoir model, since the uncertainty in the reservoir description in the interwell areas is significantly reduced.

Key concepts: Geology, Facies, Fluvial, Lithology, Reservoir modeling, Drilling, Channel (broadcasting), Petrology

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